Authors: Seyed Mohammad Gholami-Zanjani; Ruholla Jafari-Marandi; Mir Saman Pishvaee; Walid Klibi
Addresses: School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; The Centre of Excellence in Supply Chain (CESIT), KEDGE Business School, France ' Department of Industrial and Manufacturing Engineering, California Polytechnic State University, San Luis Obispo, USA ' School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran ' The Centre of Excellence in Supply Chain (CESIT), KEDGE Business School, France; Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Canada
Abstract: In recent years, the growth of technology has brought about a new range of problems, referred to as dynamic vehicle routing problems. In these problems, a part of the orders are received in advance before departure of vehicles from depots, but some new orders will come in after the vehicle's departure. Although cooperative strategy has not received considerable attention in the literature, it could be a possibility in practice which can help reduce costs. Multiple vehicles in this strategy are allowed to travel and they can transfer goods between one another when they meet in demand points so as to better satisfy the late demands. A mixed integer nonlinear mathematical model is proposed for multi-vehicle routing problem considering product transshipment between vehicles in dynamic situations. A genetic algorithm is then developed to deal with the complexity of the problem. The experimental results show that cooperative strategy is an attractive possibility to reduce unsatisfied late received demands and costs.
Keywords: cooperative strategy; dynamic vehicle routing problem; DVRP; disaster relief management; robust genetic algorithm.
International Journal of Shipping and Transport Logistics, 2019 Vol.11 No.6, pp.455 - 475
Received: 07 Feb 2018
Accepted: 20 Jul 2018
Published online: 28 Nov 2019 *